4 papers
Modeling Spatio-temporal Extremes via Conditional Variational Autoencoders
Xiaoyu Ma, Likun Zhang, Christopher K. Wikle
Extreme weather events are widely studied in fields such as agriculture, ecology, and meteorology. The spatio-temporal co-occurrence of extreme events can strengthen or weaken unde…
Modeling high and low extremes with a novel dynamic spatio-temporal model
Myungsoo Yoo, Likun Zhang, Christopher K. Wikle +1
Extreme environmental events such as severe storms, drought, heat waves, flash floods, and abrupt species collapse have become more prevalent in the earth-atmosphere dynamic system…
AutoMR: A Universal Time Series Motion Recognition Pipeline
Likun Zhang, Sicheng Yang, Zhuo Wang +2
In this paper, we present an end-to-end automated motion recognition (AutoMR) pipeline designed for multimodal datasets. The proposed framework seamlessly integrates data preproces…
Capturing Extreme Events in Turbulence using an Extreme Variational Autoencoder (xVAE)
Likun Zhang, Kiran Bhaganagar, Christopher K. Wikle
Turbulent flow fields are characterized by extreme events that are statistically intermittent and carry a significant amount of energy and physical importance. To emulate these flo…